Design experiments that isolate signal from noise in ecological data, and design tests that can increment progress forward when results are ambiguous.
Work with the CTO to prioritize intermediate outputs, publication opportunities, and risks.
Work iteratively with the CSO to test and refine modelling approaches and uncertainty quantification that can be interpreted in ecological context.
Define a standardization strategy that ensures model comparability across ecosystems and geographies.
Translate ecological hypotheses from the CSO into testable ML experiments.
Implement, train, and evaluate models that characterise ecosystem condition across multiple measurement modalities.
Contribute to research outputs: white papers, technical documentation, and peer-reviewed publications.
Working with a growing team under your management, you will develop and maintain the technical stack to ensure reproducible, rapid experimentation.
Work with the leadership team to hire and lead additional engineers and data scientists.
Evaluate and communicate needs and opportunities to creatively accelerate progress.
Establish technical standards, code review practices, and documentation norms.

Requirements

8+ years in machine learning, data engineering, or applied research with end-to-end system ownership.
Track record with machine learning infrastructure and experiment tracking, model versioning, reproducible pipelines.
Experience with multimodal data. At minimum two of time-series sensor data, audio/acoustic data, imagery, or geospatial/remote sensing.
Experience with cloud platforms (AWS or GCP) and MLOps tooling.
Demonstrated ability to scope problems, make architectural decisions, and deliver without close supervision.
Strong scientific communication. You have the ability to explain technical choices across domains and document work for reproducibility.

Benefits

Performance-based bonus

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningdata engineeringexperiment trackingmodel versioningreproducible pipelinesmultimodal datatime-series datageospatial datacloud platformsMLOps

Soft Skills

scientific communicationproblem scopingarchitectural decision makingindependent deliveryteam leadership